Solar forecasting for networked power plants

ABSTRACT

A method may include obtaining irradiance data at a first time and a second time from sensors, determining whether one or more solar modules of a plurality of networked power plants will be covered by a shadow or shade at a third time based on the irradiance data, and generating, based on the determination, a power output prediction for each power plant of the networked power plants at the third time. The method may further include receiving power delivery profiles for first and second loads, adjusting a power output of one or more power plants of the networked power plants based at least in part on the power output prediction and the power delivery profiles for the first and second loads, and allocating a combined power output of the power plants to the first and second loads based on first and second load reliability thresholds.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/972,863 filed Oct. 25, 2022, which is a continuation of U.S.application Ser. No. 17/879,270 filed Aug. 2, 2022, now U.S. Pat. No.11,489,491 which is a continuation-in-part of U.S. application Ser. No.17/742,980 filed May 12, 2022, and a continuation-in-part of U.S.application Ser. No. 17/344,706 filed Jun. 10, 2021, now U.S. Pat. No.11,451,191, which is a continuation of U.S. application Ser. No.17/210,399, filed Mar. 23, 2021, now U.S. Pat. No. 11,063,554. All ofthe above applications are incorporated by reference in their entiretyfor all they disclose.

BACKGROUND

Renewable energy power plants (REPPs) often have inconsistent orintermittent power outputs due to the nature of renewable energygeneration. Solar power plants receive variable amounts of sunlightbased on the time of day, seasonal cycles and weather patterns. Shade orshadows cast by clouds or other objects may introduce variability intopower outputs that are difficult to predict. Intermittent powerdelivery, however, is incompatible with loads or grid systems thatbalance load and production on a real time basis. What is needed is morereliable power delivery from REPPs.

SUMMARY

Aspects of the present disclosure are directed to a method includingobtaining irradiance data at a first time and a second time from aplurality of sensors, determining whether one or more solar modules of aplurality of networked power plants will be covered by a shadow or shadeat a third time based on the irradiance data, and generating, based atleast in part on the determination, a power output prediction for eachpower plant of the plurality of networked power plants at the thirdtime. The method may further include receiving a first power deliveryprofile and a first reliability threshold for a first load, receiving asecond power delivery profile and a second reliability threshold for asecond load, adjusting a power output of one or more power plants of theplurality of networked power plants based at least in part on the poweroutput prediction, the first power delivery profile, the second powerdelivery profile, the first reliability threshold, and the secondreliability threshold, and allocating a combined power output of theplurality of networked power plants to the first and second loads.

The method may further include adjusting the power output of the one ormore of the plurality of networked power plants such that the combinedpower output of the plurality of networked power plants satisfies thepower delivery profile for the first load and the power delivery profilefor the second load.

The method may further include adjusting the power output of the one ormore of the plurality of networked power plants such that a variabilityof the combined output of the plurality of networked power plants isless than a variability of an output of each power plant of theplurality of networked power plants.

The method may further include delivering the allocated combined outputto the first load and the second load via a grid, where allocating thecombined power output to the first and second loads includescommunicating to the first load a first amount of power delivered to thefirst load and communicating to the second load a second amount of powerdelivered to the second load.

The method may further include determining whether the one or more solarmodules of the plurality of networked power plants will be covered by ashadow or shade at the third time by determining a position and a shapeof the shadow or shade at the first time and the second time.

The method may further include determining whether the one or more solarmodules of the plurality of networked power plants will be covered by ashadow or shade at the third time by determining a velocity of theshadow or shade.

The method may further include adjusting the power output of the one ormore power plants of the plurality of networked power plants byadjusting a charge/discharge of an energy storage system (ESS) of theone or more power plants of the plurality of networked power plants.

Aspects of the present disclosure are directed to a system including acontroller configured to obtain irradiance data at a first time and asecond time from a plurality of sensors, determine whether one or moresolar modules of a plurality of networked power plants will be coveredby a shadow or shade at a third time based on the irradiance data, andgenerate, based at least in part on the determination, a power outputprediction for each power plant of the plurality of networked powerplants at the third time. The controller may be further configured toreceive a power delivery profile for a first load, receive a powerdelivery profile for a second load, adjust a power output of one or morepower plants of the plurality of networked power plants based at leastin part on the power output prediction, the power delivery profile forthe first load, and the power delivery profile for the second load, andallocate a combined power output of the plurality of networked powerplants to the first and second loads.

The controller may be further configured to adjust the power output ofthe one or more of the plurality of networked power plants such that thecombined power output of the plurality of networked power plantssatisfies the power delivery profile for the first load and the powerdelivery profile for the second load.

The controller may be further configured to adjust the power output ofthe one or more of the plurality of networked power plants such that avariability of the combined output of the plurality of networked powerplants is less than a variability of an output of each power plant ofthe plurality of networked power plants.

The controller may be further configured to deliver the allocatedcombined output to the first load and the second load via a grid, wherethe controller is configured to allocate the combined power output tothe first and second loads by communicating to the first load a firstamount of power delivered to the first load and communicating to thesecond load a second amount of power delivered to the second load.

The controller may be configured to determine whether the one or moresolar modules of the plurality of networked power plants will be coveredby a shadow or shade at the third time by determining a position and ashape of the shadow or shade at the first time and the second time.

The controller may be configured to determine whether the one or moresolar modules of the plurality of networked power plants will be coveredby a shadow or shade at the third time by determining a velocity of theshadow or shade.

The controller may be configured to adjust the power output of the oneor more power plants of the plurality of networked power plants byadjusting a charge/discharge of an energy storage system (ESS) of theone or more power plants of the plurality of networked power plants.

Aspects of the present disclosure are directed to a method includingobtaining irradiance data at a first time and a second time from aplurality of sensors incorporated in or adjacent a first renewableenergy power plant (REPP) determining, based on the irradiance data,whether one or more solar modules of a second REPP will be covered by ashadow or shade at a third time, and generating, based at least in parton the determination, a power output prediction for the second REPP. Themethod may further include adjusting a power of one or more of the firstREPP and the second REPP based at least in part on the power outputprediction for the second REPP and allocating a combined power output ofthe first REPP and the second REPP to a first load and a second load.

The method may further include adjusting the power output of the one ormore of the first REPP and the second REPP such that the combined poweroutput of the first REPP and the second REPP satisfies the powerdelivery profile for the first load and the power delivery profile forthe second load.

The method may further include adjusting the power output of the one ormore of the first REPP and the second REPP is adjusted such that avariability of the combined output of the first REPP and the second REPPis less than a variability of an output of the first REPP and avariability of an output of the second REPP.

The method may further include delivering the allocated combined outputto the first load and the second load via a grid, where allocating thecombined power output to the first and second loads includescommunicating to the first load a first amount of power delivered to thefirst load and communicating to the second load a second amount of powerdelivered to the second load.

The method may further include determining whether the one or more solarmodules of the plurality of networked power plants will be covered by ashadow or shade at the third time by determining a position and a shapeof the shadow or shade at the first time and the second time.

The method may further include determining whether the one or more solarmodules of the plurality of networked power plants will be covered by ashadow or shade at the third time by determining a velocity of theshadow or shade.

The method may further include adjusting the power output of the one ormore of the first REPP and the second REPP by adjusting acharge/discharge of an energy storage system (ESS) of each of the one ormore of the first REPP and the second REPP.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the present disclosure are best understood from the followingdetailed description when read with the accompanying figures. It isnoted that, in accordance with the standard practice in the industry,various features are not drawn to scale. In fact, the dimensions of thevarious features may be arbitrarily increased or reduced for clarity ofdiscussion.

FIG. 1 schematically illustrates a solar power plant, according to someembodiments of the present disclosure;

FIG. 2 is a flow chart of a process for controlling the power output ofthe solar power plant in accordance with predicted irradiance at thesolar power plant, according to some embodiments of the presentdisclosure;

FIG. 3 is a flow chart of certain sub-operations of the process of FIG.2 , according to some embodiments of the present disclosure;

FIG. 4 graphically illustrates the process of FIG. 3 ;

FIG. 5 is a flow chart of a process for adjusting the orientation ofsolar modules at the solar power plant, according to some embodiments ofthe present disclosure; and

FIG. 6 shows a computer system that is programmed or otherwiseconfigured to implement methods provided herein.

FIG. 7 illustrates an example environment in accordance with one or moreembodiments.

FIG. 8 illustrates a first renewable energy power plant (REPP) outputand a first power delivery profile.

FIG. 9 illustrates a second REPP output and a second power deliveryprofile.

FIG. 10 illustrates a combined REPP output and a combined power deliveryprofile.

FIG. 11 illustrates another example environment in accordance with oneor more embodiments.

FIG. 12 illustrates a first REPP output, a first power delivery profile,and a first excess output.

FIG. 13 illustrates a second REPP output, a second power deliveryprofile, and a second excess output.

FIG. 14 illustrates a combined excess output and a third deliveryprofile.

FIG. 15 illustrates another example environment in accordance with oneor more embodiments.

FIG. 16 is a flowchart of an example method for allocating power fromnetworked power plants in accordance with one or more embodiments.

FIG. 17 is a flowchart of an example method for delivering power using avirtual power plant in accordance with one or more embodiments.

FIG. 18 is a flowchart of an example method for delivering power fromnetworked power plants using solar forecasting.

DETAILED DESCRIPTION

Aspects of the present disclosure provide systems and methods forforecasting short-term variations in the output of a solar power plantdue to changing atmospheric conditions. In some embodiments of thepresent disclosure, a system obtains irradiance data from a plurality ofsensors disposed among or adjacent to a plurality of solar modules ofthe power plant. The system can obtain the irradiance data continuouslyor at regular intervals. If the irradiance measured by a particularsensor is less than the irradiance measured by other sensors in thearea, the solar modules near that sensor may be covered by a shadow(e.g., a cloud shadow) or shade. The system can process irradiance datacollected at a first time and at a second time to generate an outputthat indicates whether one or more solar modules of the plurality ofsolar modules will be covered by a shadow at a third time.

The output may be a data structure containing the predicted irradianceof each solar module at the third time. The system can use this outputto more accurately predict the instantaneous power output of the solarpower plant at the third time.

FIG. 1 schematically illustrates a solar power plant 100, according tosome embodiments of the present disclosure. The solar power plant 100may have solar modules 110, solar inverters 120, an energy storagesystem 130, bi-directional inverters 140, sensors 150, a computingsystem 160, and a controller 170. The solar modules 110 and the energystorage system 130 may be connected to the grid through the inverters120 and the bi-directional inverters 140.

The solar modules 110 may be arranged in a grid. Each solar module mayhave one or more photovoltaic cells that convert light to electricpower. The photovoltaic cells may be multi-, mono- or amorphous siliconcells, cadmium telluride cells, perovskite cells, or the like. Thephotovoltaic cells may be single junction or multi junction cells. Thesolar modules 110 may be mono-facial or bifacial.

The inverters 120 may be direct current-to-alternating current(DC-to-AC) inverters. The inverters 120 can convert DC power generatedby the solar modules 110 to AC power for the grid.

The energy storage system 130 may be a compressed air system, a pumpedwater system, or a battery-based system. The energy storage system 130can store excess power generated by the solar modules 110 or availablefrom the grid (e.g., during low demand periods). Additionally oralternatively, the energy storage system 130 can be discharged in orderto provide additional power to the grid (e.g., when grid demand is high,or when the power output of the solar modules is low). Thebi-directional inverters 140 may be DC-to-AC and AC-to-DC inverters,that facilitate discharging and charging of the energy storage system130, respectively.

The sensors 150 may include irradiance meters. The sensors 150 may alsoinclude wind speed sensors, precipitation sensors, humidity sensors, andthe like. The sensors 150 may be communicatively coupled to thecomputing system 160. The computing system 160 may have a database 162and a processor 164. The computing system 160 can store the datagenerated by the sensors 150 in the database 162. The processor 164 canobtain the data from the database 162 and process the data to generatepredictions, including irradiance and/or cloud predictions, powerpredictions, and the like. The process of generating these predictionsis described in greater detail in FIGS. 2-5 . The controller 170 can usethe predictions generated by the computing system 160 to control thepower output of the solar modules 110 and the energy storage system 130.For example, if the predictions indicate that cloud coverage will reducethe power output of the solar modules 110, the controller 170 can sendcontrol signals that cause the energy storage system 130 andbi-directional inverters 140 to discharge power to the grid. Or, if thepredictions indicate that the solar modules 110 will generate excesspower, the controller 170 can send control signals that cause one ormore of the solar modules 110 to disconnect from the grid and connectinstead to the energy storage system 130 to charge the energy storagesystem 130 with the excess power. The controller 170 can also controlthe orientation of the solar panels.

The computing system 160 can be implemented on one or more computingdevices. The computing devices can be servers, desktop or laptopcomputers, electronic tablets, mobile devices, or the like. Thecomputing devices can be located in one or more locations. The computingdevices can have general-purpose processors, graphics processing units(GPU), application-specific integrated circuits (ASIC),field-programmable gate-arrays (FPGA), or the like. The computingdevices can additionally have memory, e.g., dynamic or staticrandom-access memory, read-only memory, flash memory, hard drives, orthe like. The memory can be configured to store instructions that, uponexecution, cause the computing devices to implement the functionality ofthe subsystems. The computing devices can additionally have networkcommunication devices. The network communication devices can enable thecomputing devices to communicate with each other and with any number ofuser devices, over a network. The network can be a wired or wirelessnetwork. For example, the network can be a fiber optic network,Ethernet® network, a satellite network, a cellular network, a Wi-Fi®network, a Bluetooth® network, or the like. In other implementations,the computing devices can be several distributed computing devices thatare accessible through the Internet. Such computing devices may beconsidered cloud computing devices.

FIG. 2 is a flow chart of a process 200 for controlling the power outputof a solar power plant in accordance with predicted irradiance at thepower plant, according to some embodiments of the present disclosure.The process 200 can be performed by a system of one or moreappropriately programmed computers in one or more locations (e.g., thecomputing system 160 and the controller 170 of FIG. 1 ).

The solar power plant may have plurality of solar modules. The solarmodules may be arranged in a grid. Each solar module may have one ormore photovoltaic cells that convert light to electric power. Thephotovoltaic cells may be multi-, mono- or amorphous silicon cells,cadmium telluride cells, perovskite cells, or the like. The photovoltaiccells may be single junction or multi junction cells. The solar modulesmay be mono-facial or bifacial. The solar modules may also have powerelectronics. For example, each solar module—or a subset of solarmodules—may have a DC-to-DC converter and an inverter. The DC-to-DCconverters can adjust the voltage of the DC power generated by the solarmodules, and the inverters can convert the DC power generated by thesolar modules to AC power. Each solar module may also have a controllerand a motor for adjusting the orientation of the solar module withrespect to the sun.

The solar power plant may also have an energy storage system. The energystorage system may be a compressed air system, a pumped water system, ora battery-based system, for example. The energy storage systems canstore excess power generated by the solar power plant when grid demandis low and supplement power generated by the solar modules when griddemand is high.

In an operation of the process 200, the system can obtain irradiancedata from a plurality of sensors at a first time and at a second time(210). The sensors may be disposed among or adjacent to the solarmodules. For example, the sensors may be disposed between the solarmodules and along or adjacent to the perimeter of the grid of solarmodules. There may be at least about 1 solar module per sensor, 2 solarmodules per sensor, 3 solar modules per sensor, 4 solar modules persensor, 5 solar modules per sensor, 10 solar modules per sensor, 20solar modules per sensor, or more. The sensors may be irradiance meters.Alternatively, the inverters that are used to covert the DC powergenerated by the solar modules to AC power may be used as sensors. Theinverters may be disposed among the array of solar modules, and aparticular inverter may be connected to a subset of adjacent solarmodules. The inverters may have built-in sensors that are configured tomeasure electric power. For example, the sensors may be components of asupervisory control and data acquisition (SCADA) system of theinverters. The irradiance of the solar modules that are connected to aparticular inverter can be inferred from the power output of thatinverter. The use of inverters as sensors may be advantageous because itmay allow the implementation of the forecasting system described hereinwithout specialized or dedicated hardware.

The second time may be at least about 1 minute, 2 minutes, 3 minutes, 4minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 45 minutes, 1hour, or more after the first time. The second time may be at most about1 hour, 45 minutes, 30 minutes, 15 minutes, 10 minutes, 5 minutes, 4minutes, 3 minutes, 2 minutes, 1 minute, or less after the first time.

The system can process the irradiance data at the first time and thesecond time to generate an output that indicates whether one or moresolar modules will be covered by a shadow or shade at a third time(220). The shadow may be caused by a cloud or other atmosphericcondition or phenomena (e.g., fog, dust, smog, or the like). The outputmay be or include a data structure that comprises the predicted orexpected irradiance of each solar module at the third time. The datastructure may be a map that is superimposed on a representation of thegrid of solar modules. Alternatively, the output may merely indicatewhich solar modules are expected to be covered by the shadow.

The third time may be at least about 1 minute, 2 minutes, 3 minutes, 4minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 45 minutes, 1hour, 2 hours, or more after the second time. The second time may be atmost about 2 hours, 1 hour, 45 minutes, 30 minutes, 15 minutes, 10minutes, 5 minutes, 4 minutes, 3 minutes, 2 minutes, 1 minute, or lessafter the second time.

FIG. 3 is a flow chart of the sub-operations of operation 220, accordingto some embodiments of the present disclosure. The system can determinethe position and shape of the shadow at the first time (310).Determining the position and shape of the shadow may comprisedetermining the edges of the shadow, including the leading and trailingedges and any other edges. The system can determine the edges of theshadow by processing the irradiance data with an edge detectionalgorithm. The edge detection algorithm may compute derivatives of theirradiance values in the irradiance data to determine locations in whichthe irradiance values exhibit a high rate of change. Such locations maycorrespond to the edges of the shadow. Alternatively, the edge detectionalgorithm may be a supervised machine learning algorithm (e.g., aconvolutional neural network). The supervised machine learning algorithmmay be trained to detect the edges of the shadow. The supervised machinelearning algorithm may be trained on labeled training examples. Thelabeled training examples may be, for example, maps of irradiance datain which the edges of the shadows or shade have been identified. Thesystem can then determine the position and shape of the shadow at thesecond time (320). Operation 320 may be substantially the same asoperation 310.

Based on the position and shape of the shadow at the first time, theposition and shape of the shadow at the second time, and the differencebetween the first time and the second time, the system can determine thevelocity of the shadow (330). The system can predict the position andshape of the shadow at the third time based at least in part on itsvelocity and its position and shape at the second time (340).Determining the position and shape at the third time may compriseapplying an inertia model or vector analysis to the velocity and theposition at the second time. In predicting the position and shape of theshadow at the third time, the system can also consider the current windspeed.

Based at least in part on the predicted position and shape of the shadowat the third time, the system can generate the output that indicateswhether one or more solar modules will be covered by the shadow at thethird (350). As mentioned above, the output may be or include a datastructure that comprises the predicted or expected irradiance of eachsolar module at the third time. The expected irradiance of a particularsolar module at the third time may be inferred from the actualirradiance of a similarly-situated solar module at the second time(e.g., from the actual irradiance of a solar module that was covered bythe same shadow that is expected to cover the particular solar module atthe third time). Alternatively, the output may merely indicate whichsolar modules are expected to be covered by the shadow.

FIG. 4 graphically illustrates the process 300. 410 represents theoutput of an array of irradiance meters at a first time, with the shadedboxes representing lower irradiance values. 420 represents the output ofthe array of irradiance meters at a second time. In 420, additionalboxes are shaded, indicating the movement of shadow to right. 430represents predicted irradiance values at a third time.

Returning to FIG. 2 , the system can generate a prediction of the poweroutput of the solar power plant at the third time based at least in parton the output generated in operation 220 (230). In general, the poweroutput of a particular solar module may be defined by the equation:

P=A×I×R×PR,

where P is the power output of the solar module in watts, A is the areaof the solar module in square meters, I is the irradiance of the solarmodule in watts per square meter, R is the yield of the solar module,and PR is the performance ratio. The yield of the solar module may bethe efficiency of the solar module in converting light to power. Theperformance ratio of the solar module may account for other types oflosses, including inverter losses, temperature losses, cable losses, andthe like. The yield and performance ratios of the solar modules may bedetermined empirically. The yield and performance ratios may varydepending on the age of the solar modules and numerous other factors(e.g., irradiance). Such factors may be considered when computing theexpected power outputs of the solar modules.

The power output of the solar power plant may be the sum of the poweroutputs of the individual solar modules. To predict the power output ofthe solar power plant at the third time, the system can use thepredicted irradiance of each solar module at the third time in theabove-mentioned equation.

In some cases, the predicted power output of the solar power plant atthe third time may be different than the actual power output of thepower plant at the second time. For example, the predicted power outputat the third time may be less than the actual power output at the secondtime due to an incoming cloud shadow. Alternatively, the predicted poweroutput at the third time may be greater than the actual power output ofthe power plant at the second time due to an outgoing cloud shadow. Itmay be desirable to prevent a change in the power output of the powerplant or to increase or decrease the power output slowly rather thanabruptly.

Accordingly, in some embodiments, the system can take one or moreactions to (i) prevent the power output of the power plant from changingor (ii) reduce the rate of change of the power output (240). Forexample, the system can send a control signal to an energy storagesystem at the power plant. The control signal may cause the energystorage system to store excess power generated by the solar modules, orit may cause the energy storage system to provide power to supplementthe power generated by the solar modules. Utilizing the energy storagesystem in this way may ensure that the power output of the solar powerplant remains steady over time. In some cases, an increase or decreasein the power output of the solar power plant may be acceptable. In suchcases, the energy storage system may be used to slowly ramp the poweroutput of the solar power plant up or down, which may be more desirablethan an abrupt change. Even in the absence of an energy storage system,the power output of the solar array itself can be reduced to less thanit is capable of delivering (e.g., by instructing the inverters to limittheir power output).

In some embodiments, the system can merely notify a grid operator of theexpected increase or decrease in power output (250). Thereafter, thegrid operator can address the change in power output as it sees fit.

The solar modules described herein may be disposed on solar trackers.The solar trackers can be used to adjust the orientation of the solarmodules to minimize the angle of incidence between the solar modules andincoming sunlight. On clear days, the solar trackers may orient thesolar modules so that they face the sun directly. However, on cloudydays, the solar trackers may instead orient the solar modules parallelto the ground, because the intensity of diffuse light may exceed theintensity of direct light on cloudy days.

The solar trackers may allow the solar modules to rotate about one ortwo axes. The solar trackers may have motors to facilitate the rotation.A solar tracking algorithm may control the motors. The solar trackingalgorithm may be a date and time-based algorithm, or it may use sensorinputs. The solar tracking algorithm may be a machine learningalgorithm. For example, the solar tracking algorithm may be areinforcement learning algorithm.

FIG. 5 is a flow chart of a process 500 for adjusting the orientation ofsolar modules, according to some embodiments of the present disclosure.The process 500 can be performed by a system of one or moreappropriately programmed computers in one or more locations (e.g., thecomputing system 160 and the controller 170 of FIG. 1 ).

The system can obtain irradiance data from a plurality of sensors at afirst time and at a second time (510). The sensors may be irradiancemeters. Additionally or alternatively, the inverters that convert DCpower generated by the solar modules to AC power may serve as sensors.Operation 510 of the process 500 may be substantially the same as theoperation 210 of the process 200.

The system can process the irradiance data at the first time and thesecond time to generate an output that indicates whether one or moresolar modules will be covered by a shadow or shade at a third time(520). The output may be or include a data structure that comprises thepredicted or expected irradiance of each solar module at the third time.The data structure may be a map that is superimposed on a representationof the grid of solar modules. Alternatively, the output may merelyindicate which solar modules are expected to be covered by the shadow.Operation 520 of the process 500 may be substantially the same as theoperation 510 of the process 200.

The system can then use the output of operation 520 as input to thesolar tracking algorithm described above (530). The output of the solartracking algorithm may be a control signal that causes one or more solartrackers to adjust the orientation of one or more solar modules based onpredicted cloud patterns. If the system predicts that particular solarmodules will be covered by a cloud shadow at a future time, the solartracking algorithm can adjust the orientation of those solar modules tobe substantially parallel to the ground. This may be desirable becausethe intensity of diffuse light may exceed the intensity of direct lightin cloudy conditions. If the system predicts that particular solarmodules will not be covered by a cloud shadow at a future time, thesolar tracking algorithm can adjust the orientation of those solarmodules to be perpendicular to the sun. If the system predicts partialor broken cloud cover, the solar tracking algorithm can adjust theorientation of the solar modules to face bright areas between clouds.The system can make these adjustments immediately prior to the leadingor trailing edge of a cloud shadow reaching the relevant solar modules.In some cases, the velocity of clouds may be so high that it isimpossible or uneconomic to adjust the orientation of the solar modules.In such cases, solar tracking may be halted.

Machine Learning

The present disclosure describes an edge detection algorithm fordetecting the edges of a cloud shadow. The edge detection algorithm maybe a supervised machine learning algorithm. The supervised machinelearning algorithm may be trained on historical data. The historicaldata may include (i) instances of irradiance data at a particular timeand (ii) for each instance, the manually identified edges of any cloudshadows in the irradiance data. The supervised machine learningalgorithm may be trained by providing the instances of irradiance datato an untrained or partially trained version of the algorithm togenerate predicted outputs that indicate the edges of any cloud shadowsin the irradiance data. The predicted outputs can be compared to theknown outputs (i.e., the manually identified edges of any cloud shadowsin the irradiance data), and if there is a difference, the parameters ofthe supervised machine learning algorithm can be updated. The supervisedmachine learning algorithm may be a regression algorithm, a supportvector machine, a decision tree, a neural network, or the like. In casesin which the machine learning algorithm is a regression algorithm, theweights may be regression parameters.

In some cases, the supervised machine learning algorithm may be a neuralnetwork. Neural networks may employ multiple layers of operations topredict one or more outputs, e.g., the edge of a shadow. Neural networksmay include one or more hidden layers situated between an input layerand an output layer. The output of each layer can be used as input toanother layer, e.g., the next hidden layer or the output layer. Eachlayer of a neural network may specify one or more transformationoperations to be performed on input to the layer. Such transformationoperations may be referred to as neurons. The output of a particularneuron may be a weighted sum of the inputs to the neuron, adjusted witha bias and multiplied by an activation function, e.g., a rectifiedlinear unit (ReLU) or a sigmoid function. Training a neural network mayinvolve providing inputs to the untrained neural network to generatepredicted outputs, comparing the predicted outputs to expected outputs,and updating the algorithm's weights and biases to account for thedifference between the predicted outputs and the expected outputs.Specifically, a cost function may be used to calculate a differencebetween the predicted outputs and the expected outputs. By computing thederivative of the cost function with respect to the weights and biasesof the network, the weights and biases may be iteratively adjusted overmultiple cycles to minimize the cost function. Training may be completewhen the predicted outputs satisfy a convergence condition, e.g., asmall magnitude of calculated cost as determined by the cost function.

The neural network may be a convolutional neural network (CNN). CNNs areneural networks in which neurons in some layers, called convolutionallayers, receive input from only a small portion of the input data set(e.g., a small area of irradiance data). These small portions may bereferred to as the neurons' receptive fields. Each neuron in such aconvolutional layer may have the same weights. In this way, theconvolutional layer can detect certain features in any portion of theinput data set. CNNs may also have pooling layers that combine theoutputs of neuron clusters in convolutional layers and fully connectedlayers that are similar to traditional layers in a feed-forward neuralnetwork. CNNs may be particularly adept at classifying images orimage-like data (e.g., a map of irradiance data).

Alternatively, the edge detection algorithm may be an unsupervisedmachine learning algorithm. The unsupervised machine learning algorithmmay be capable of identifying patterns in irradiance data (e.g., areasof the irradiance data that exhibit a high rate of change). Theunsupervised machine learning algorithm may be a clustering algorithm,an isolation forest, an autoencoder, or the like.

The present disclosure also describes a solar tracking algorithm. Thesolar tracking algorithm may be a reinforcement learning algorithm. Thereinforcement learning algorithm may seek an optimal solution to aproblem by balancing exploration of uncharted territory withexploitation of current knowledge. In reinforcement learning, labeledinput-output pairs need not be used. Instead, an action is chosen from aset of available actions. The action may result in a new environmentalstate (i.e., a new solar module orientation). The new environmentalstate may have a reward associated with it, and the reward may bepositive or negative depending on whether the new state is better (i.e.,if the solar module generates more power) or worse (i.e., if the solarmodule generates less power) than the previous state. The goal of theagent may be to collect as much reward as possible, i.e., optimize theoutput power of the solar module.

Computer Systems

The present disclosure provides computer systems that are programmed toimplement methods of the disclosure. FIG. 6 shows a computer system 601that is programmed or otherwise configured to generate an output thatindicates whether one or more solar modules will be covered by a shadowor shade, and to use the output to predict the power output of a solarplant or adjust the orientation of the solar modules. The computersystem 601 can be an electronic device of a user or a computer systemthat is remotely located with respect to the electronic device. Theelectronic device can be a mobile electronic device.

The computer system 601 includes a central processing unit (CPU, also“processor” and “computer processor” herein) 605, which can be a singlecore or multi core processor, or a plurality of processors for parallelprocessing. The computer system 601 also includes memory or memorylocation 610 (e.g., random-access memory, read-only memory, flashmemory), electronic storage unit 615 (e.g., hard disk), communicationinterface 620 (e.g., network adapter) for communicating with one or moreother systems, and peripheral devices 625, such as cache, other memory,data storage and/or electronic display adapters. The memory 610, storageunit 615, interface 620 and peripheral devices 625 are in communicationwith the CPU 605 through a communication bus (solid lines), such as amotherboard. The storage unit 615 can be a data storage unit (or datarepository) for storing data. The computer system 601 can be operativelycoupled to a computer network (“network”) 630 with the aid of thecommunication interface 620. The network 630 can be the Internet, aninternet and/or extranet, or an intranet and/or extranet that is incommunication with the Internet. The network 630 in some cases is atelecommunication and/or data network. The network 630 can include oneor more computer servers, which can enable distributed computing, suchas cloud computing. The network 630, in some cases with the aid of thecomputer system 601, can implement a peer-to-peer network, which mayenable devices coupled to the computer system 601 to behave as a clientor a server.

The CPU 605 can execute a sequence of machine-readable instructions,which can be embodied in a program or software. The instructions may bestored in a memory location, such as the memory 610. The instructionscan be directed to the CPU 605, which can subsequently program orotherwise configure the CPU 605 to implement methods of the presentdisclosure. Examples of operations performed by the CPU 605 can includefetch, decode, execute, and writeback.

The CPU 605 can be part of a circuit, such as an integrated circuit. Oneor more other components of the system 601 can be included in thecircuit. In some cases, the circuit is an application specificintegrated circuit (ASIC).

The storage unit 615 can store files, such as drivers, libraries andsaved programs. The storage unit 615 can store user data, e.g., userpreferences and user programs. The computer system 601 in some cases caninclude one or more additional data storage units that are external tothe computer system 601, such as located on a remote server that is incommunication with the computer system 601 through an intranet or theInternet.

The computer system 601 can communicate with one or more remote computersystems through the network 630. For instance, the computer system 601can communicate with a remote computer system of a user. Examples ofremote computer systems include personal computers (e.g., portable PC),slate or tablet PC's (e.g., Apple® iPad, Samsung® Galaxy Tab),telephones, Smart phones (e.g., Apple® iPhone, Android-enabled device,Blackberry®), or personal digital assistants. The user can access thecomputer system 601 via the network 630.

Methods as described herein can be implemented by way of machine (e.g.,computer processor) executable code stored on an electronic storagelocation of the computer system 601, such as, for example, on the memory610 or electronic storage unit 615. The machine executable ormachine-readable code can be provided in the form of software. Duringuse, the code can be executed by the processor 605. In some cases, thecode can be retrieved from the storage unit 615 and stored on the memory610 for ready access by the processor 605. In some situations, theelectronic storage unit 615 can be precluded, and machine-executableinstructions are stored on memory 610.

The code can be pre-compiled and configured for use with a machinehaving a processer adapted to execute the code or can be compiled duringruntime. The code can be supplied in a programming language that can beselected to enable the code to execute in a pre-compiled or as-compiledfashion.

Aspects of the systems and methods provided herein, such as the computersystem 601, can be embodied in programming. Various aspects of thetechnology may be thought of as “products” or “articles of manufacture”typically in the form of machine (or processor) executable code and/orassociated data that is carried on or embodied in a type of machinereadable medium. Machine-executable code can be stored on an electronicstorage unit, such as memory (e.g., read-only memory, random-accessmemory, flash memory) or a hard disk. “Storage” type media can includeany or all of the tangible memory of the computers, processors or thelike, or associated modules thereof, such as various semiconductormemories, tape drives, disk drives and the like, which may providenon-transitory storage at any time for the software programming. All orportions of the software may at times be communicated through theInternet or various other telecommunication networks. Suchcommunications, for example, may enable loading of the software from onecomputer or processor into another, for example, from a managementserver or host computer into the computer platform of an applicationserver. Thus, another type of media that may bear the software elementsincludes optical, electrical and electromagnetic waves, such as usedacross physical interfaces between local devices, through wired andoptical landline networks and over various air-links. The physicalelements that carry such waves, such as wired or wireless links, opticallinks or the like, also may be considered as media bearing the software.As used herein, unless restricted to non-transitory, tangible “storage”media, terms such as computer or machine “readable medium” refer to anymedium that participates in providing instructions to a processor forexecution.

Hence, a machine readable medium, such as computer-executable code, maytake many forms, including but not limited to, a tangible storagemedium, a carrier wave medium or physical transmission medium.Non-volatile storage media include, for example, optical or magneticdisks, such as any of the storage devices in any computer(s) or thelike, such as may be used to implement the databases, etc. shown in thedrawings. Volatile storage media include dynamic memory, such as mainmemory of such a computer platform. Tangible transmission media includecoaxial cables; copper wire and fiber optics, including the wires thatcomprise a bus within a computer system. Carrier-wave transmission mediamay take the form of electric or electromagnetic signals, or acoustic orlight waves such as those generated during radio frequency (RF) andinfrared (IR) data communications. Common forms of computer-readablemedia therefore include for example: a floppy disk, a flexible disk,hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD orDVD-ROM, any other optical medium, punch cards paper tape, any otherphysical storage medium with patterns of holes, a RAM, a ROM, a PROM andEPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wavetransporting data or instructions, cables or links transporting such acarrier wave, or any other medium from which a computer may readprogramming code and/or data. Many of these forms of computer readablemedia may be involved in carrying one or more sequences of one or moreinstructions to a processor for execution.

The computer system 601 can include or be in communication with anelectronic display 635 that comprises a user interface (UI) 640.Examples of UI's include, without limitation, a graphical user interface(GUI) and web-based user interface.

Embodiments of the present disclosure allow an operator of networkedREPPs to deliver power with greater reliability. Combining the outputsof REPPs whose outputs are not entirely correlated results in a combinedoutput with a variability and intermittency lower than the variabilitiesand intermittencies of the outputs of the individual REPPs. This meansthat power can be delivered more consistently by networked REPPs than byindividual REPPs. Additionally, some load operators may want to use onlyrenewable energy but may require consistent power delivery. These loadoperators may want to receive power over a grid and only use renewableenergy. These load operators may correlate their power usage withrenewable power production in order to only use renewable energy. Theseload operators may send a power delivery profile to a renewable energysource representing a request for amounts of renewable power productionat different times. If the power delivery profile of a load issatisfied, the load operator can claim to only use renewable energy forthe load. The REPP output allocated to a load may be thought of as anoverlay on top of the rest of the power delivered on the grid because itis considered to be produced at the REPP and delivered to the load,ignoring the inevitable commingling of power on the grid from differentsources. The output is effectively produced at the REPP and delivered tothe load, despite the inevitable commingling of power on the grid fromdifferent sources

To consistently satisfy the power delivery profile, consistent powerdelivery is required. Individual REPPs may struggle to provideconsistent power delivery. This means that some loads may have to usesome power from non-renewable power sources or the REPP may have to havea power capacity greatly exceeding the power delivery profile of a loadin order to consistently satisfy the load's power delivery profiledespite fluctuations in power generation. Networked REPPs may be able toprovide more-consistent power that comes entirely from renewable powersources. Additionally, and/or alternatively, each REPP may have a powercapacity lower than what would be needed for a single REPP to provideconsistent power. Each REPP having a lower power capacity than what asingle, un-networked REPP would need to provide consistent power resultsin increases in efficiency and lower costs for constructing REPPs due toeach REPP needing less excess capacity which would usually not be fullyutilized. Networked REPPs may also produce power in excess of what isrequired by various loads. This excess power may be treated as a virtualREPP, or virtual power plant which can deliver power to additionalloads.

The outputs of networked REPPs and virtual power plants may be deliveredover the grid and allocated to various loads. This allocated combinedoutput of networked REPPs may be thought of as an overlay on top of therest of the power delivered on the grid because it is effectivelyproduced at the networked REPPs and delivered to the various loads towhich it is allocated, ignoring the inevitable commingling of power onthe grid from different sources. This overlay may be treated as a greengrid, utilizing the existing infrastructure of the grid, but deliveringrenewable power from REPPs to the various loads. The green grid mayfunction similar to the grid on which it operates, with a market forrenewable power distinct from a market for conventional power. The greengrid may be owned and operated by one entity, or it may include REPPsowned and operated by a variety of entities.

FIG. 7 illustrates an example environment 700 in accordance with one ormore embodiments. The environment 700 may include a first load 710, asecond load 720, a grid 730, a first power plant 740, a second powerplant 750, a network 760, and a controller 770. The first load 710 andthe second load 720 may be electrically coupled to the grid 730. Thefirst load 710 and the second load 720 may be remote from each other andhave separate power requirements. The first load 710 may have a firstpower delivery profile which details power requirements for the firstload 710 at different times. The second load 720 may have a second powerdelivery profile which details power requirements for the second load720 at different times. In some embodiments, the grid 730 may be autility grid owned and operated by a single utility or system operator.In other embodiments, the grid 730 may be a plurality of electricalconnections allowing for the transmission of power from the first powerplant 740 and the second power plant 750 to the first load 710 and thesecond load 720.

The first power plant 740 may be a first renewable energy power plant(REPP). The second power plant 750 may be a second REPP. Examples ofREPPs include, but are not limited to, solar plants, wind plants,geothermal plants, and biomass plants. REPPs may include energy storagesystems (ESSs). An example of an ESS is a battery. A battery-based ESSmay be called a batter ESS or BESS. The first power plant 740 may have afirst power output that varies over time. The second power plant 750 mayhave a second power output that varies over time. The first power outputand the second power output may vary differently such that they are nottightly correlated. For example, the first power plant 740 may begeographically remote from the second power plant 750 such that weatherpatterns at the first power plant 740 differ from weather patterns atthe second power plant 750. Thus, variation in the first power outputwill not be tightly correlated with variation in the second poweroutput. The less correlated the output of the first power plant 740 withthe output of the second power plant 750, the greater the effects ofnetworking. The less correlated the outputs of the first power plant 740and the second power plant 750, the less variation will be present inthe combined output of the first power plant 740 and the second powerplant 750. Less variation in the combined output may result in morereliability in satisfying the power delivery profiles of the first load710 and the second load 720. Less variation in the combined output mayresult in lower capacity requirements for the first power plant 740 andthe second power plant 750.

In some embodiments, the first power plant 740 and the second powerplant 750 may be selected to be networked. The first power plant 740 andthe second power plant 750 may be selected for networking based on alevel of correlation between the first power output and the second poweroutput. The first power plant 740 and the second power plant 750 may beselected for networking based on a determination that the first poweroutput and the second power output are the least correlated of aplurality of power outputs of a plurality of power plants. In someembodiments, the first power output is compared to a plurality of poweroutputs to select the second power output which is the least correlatedwith the first power output of the plurality of power outputs. In otherembodiments, the first power plant 740 and the second power plant 750may be selected by optimizing for minimized correlation from a pluralityof power plants. The controller 770 may select the first power plant 740and the second power plant 750. In some embodiments, the plurality ofpower outputs are available power outputs of a plurality of powerplants. For example, a first power output may be less correlated with asecond power output than with a third power output, but if the secondpower output is unavailable, the first and third power outputs may beselected for networking.

Similar network advantages may be realized by selecting loads with powerrequirements that are not tightly correlated. For example, a combinedpower delivery profile of two loads will have less variability than theindividual power delivery profiles of the two loads if the individualpower delivery profiles are not tightly correlated. Less variability inthe combined power delivery profile allows for the combined powerdelivery profile to be served by a power plant or network of powerplants having less excess capacity.

The first power plant 740 and the second power plant 750 may communicatewith a controller 770 via a network 760. The network 760 may be anylocal area network (LAN) or wide area network (WAN). In someembodiments, the network is the internet. In other embodiments, thenetwork is a private communications network. The controller may includea processor and a memory.

The controller 770 may control the first power plant 740 and the secondpower plant 750. The controller 770 may coordinate the first poweroutput of the first power plant 740 and the second power output of thesecond power plant 750 in order to deliver power to the first load 710and the second load 720. The controller 770 may receive the first powerdelivery profile of the first load 710 and the second power deliveryprofile of the second load 720. In some embodiments, the controller 770receives the first power delivery profile from the first load 710 andthe second power delivery profile from the second load 720 via thenetwork 760. In other embodiments, the controller 770 receives the firstpower delivery profile and the second power delivery profile fromanother source. The controller 770 may direct the first power plant 740to direct power to the first load 710 or the second load 720. Thecontroller 770 may direct the second power plant 750 to direct power tothe first load 710 or the second load 720. The controller 770 may directthe first power plant 740 to direct a first portion of its power outputto the first load 710 and a second portion of its power output to thesecond load 720. The controller 770 may direct the second power plant750 to direct a third portion of its power output to the first load 710and a fourth portion of its power output to the second load 720. In someembodiments, directing power from a power plant to a load isaccomplished by sending power from the power plant to the grid andcommunicating to the load how much power was sent to the grid. The loaddraws power from the grid equal to how much power the power plant sentto the grid. The load may match its energy consumption in a time windowto the energy sent from the power plant to the grid in the time window.The time window may be a year, a month, a day, an hour, a minute, or anyother unit of time. Where power is directed to the load from multiplepower plants, the load may match its power consumption in a time windowto the total power sent by the multiple power plants in the time window.Where the load needs to consume more energy than the total energy sentby the multiple power plants in the time window, the load operator maydraw energy from other sources (which may not be renewable) and keep arecord of the portion of energy consumed from the multiple power plantsand from the other sources respectively, as input to an algorithm thatwill adjust its future requests for energy from the multiple powerplants.

The controller 770 may direct the first power plant 740 and the secondpower plant 750 to direct power to the first load 710 and the secondload 720 to satisfy the first power delivery profile and the secondpower delivery profile. If the power output of the first power plant 740is sufficient to satisfy the first power delivery profile of the firstload 710 and the power output of the second power plant 750 issufficient to satisfy the second power delivery profile of the secondload 720, the controller 770 may direct the first power plant 740 todirect sufficient power to the first load 710 to satisfy the first powerdelivery profile and direct the second power plant 750 to directsufficient power to the second load 720 to satisfy the second powerdelivery profile. If the power output of the first power plant 740 isinsufficient to satisfy the first power delivery profile of the firstload 710 and the power output of the second power plant 750 issufficient to satisfy the second power delivery profile of the secondload 720, the controller 770 may direct the first power plant 740 todirect its power output to the first load 710 and direct the secondpower plant 750 to direct sufficient power to the second load 720 tosatisfy the second power delivery profile and an amount of power to thefirst load 710 sufficient, when combined with the power output of thefirst power plant 740, to satisfy the first power delivery profile ofthe first load 710. Since the power outputs of the first power plant 740and the second power plant 750 are not correlated, it is likely that ifthe power output of the first power plant 740 is insufficient to satisfythe first power delivery profile, the second power plant 750 hassufficient power output in excess of what is require by the second powerdelivery profile to supplement the power output of the first power plant740 to satisfy the first power delivery profile.

FIG. 8 illustrates a first renewable energy power plant (REPP) output810 and a first power delivery profile 820. The first REPP output 810 isshown by the dotted line and the first power delivery profile 820 isshown by the solid line. The first REPP output 810 may be the poweroutput of the first power plant 740 of FIG. 7 and the first powerdelivery profile 820 may be the first power delivery profile of thefirst load 710 of FIG. 7 . The first power delivery profile 820represents the power requirements of the first load 710. The first REPPoutput 810 varies over time. When the first REPP output 810 is greaterthan the first power delivery profile 820, the first REPP output 810satisfies the first power delivery profile 820. The first REPP output810 satisfies the first power delivery profile 820 for twenty oftwenty-four hours, meaning the first REPP output 810 satisfies the firstpower delivery profile 820 83% of the time. The first power plant 740may be 83% reliable based on the first REPP output 810 satisfying thefirst power delivery profile 820 of the first load 710 83% of the time.

The first load 710 may require that the first power plant 740 satisfythe first power delivery profile 820 for a number of hours or bereliable above a threshold reliability. The first REPP output 810 mayhave a maximum value much greater than a maximum value of the firstpower delivery profile 820 in order to ensure the first power plant 740is reliable above the threshold reliability. The maximum value of thefirst REPP output 810 much greater than the maximum value of the firstpower delivery profile 820 may be necessary to ensure the first powerdelivery profile 820 is satisfied given variation in the first REPPoutput 810.

FIG. 9 illustrates a second REPP output 910 and a second power deliveryprofile 920. The second REPP output 910 is shown by the dotted line andthe second power delivery profile 920 is shown by the solid line. Thesecond REPP output 910 may be the power output of the second power plant750 of FIG. 7 and the second power delivery profile 920 may be thesecond power delivery profile of the second load 720 of FIG. 7 . WhileFIG. 2 illustrates the second power delivery profile 920 as being thesame as the first power delivery profile 220, the first power deliveryprofile 220 and the second power delivery profile 920 may be different.The second power delivery profile 920 represents the power requirementsof the second load 720. The second REPP output 910 varies over time.When the second REPP output 910 is greater than the second powerdelivery profile 920, the second REPP output 910 satisfies the secondpower delivery profile 920. The second REPP output 910 satisfies thesecond power delivery profile 920 for twenty of twenty-four hours,meaning the second REPP output 910 satisfies the second power deliveryprofile 920 83% of the time. The second power plant 750 may be 83%reliable based on the second REPP output 910 satisfying the second powerdelivery profile 920 of the second load 720 83% of the time.

The second load 720 may require that the second power plant 750 satisfythe second power delivery profile 920 for a number of hours or bereliable above a threshold reliability. The second REPP output 910 mayhave a maximum value much greater than a maximum value of the secondpower delivery profile 920 in order to ensure the second power plant 750is reliable above the threshold reliability. The maximum value of thesecond REPP output 910 much greater than the maximum value of the secondpower delivery profile 920 may be necessary to ensure the second powerdelivery profile 920 is satisfied given variation in the second REPPoutput 910.

FIG. 10 illustrates a combined REPP output 1010 and a combined powerdelivery profile 1020. The combined REPP output 1010 represents acombination of the first REPP output 210 and the second REPP output 310.The combined power delivery profile 1020 represents a combination of thefirst power delivery profile 220 and the second power delivery profile320. The combined REPP output 1010 satisfies the combined power deliveryprofile 1020 twenty-two of twenty-four hours, or 92% of the time. Thismeans that the combined REPP output 1010 is more reliable than the firstpower plant 740 and the second power plant 750. This is because thefirst REPP output 210 and the second REPP output 310 are not exactlycorrelated, so there is less variability in the combined REPP output1010 than in the first REPP output 210 and the second REPP output 310.The combined REPP output 1010 can satisfy the power delivery profiles ofthe first load 710 and the second load 720 more often than the firstREPP output 210 and the second REPP output 310 when not combined. Thismeans that the first load 710 and the second load 720 can more reliablyreceive power from the first power plant 740 and the second power plant750.

For example, if operators of the first load 710 and the second load 720want to use only renewable power, the first load 710 can specify itspower needs in the first power delivery profile 220 and the second load720 can specify its power needs in the second power delivery profile320. If the first load 710 receives power only from the first powerplant 740, then the first power delivery profile 220 is only satisfied83% of the time and the first load 710 can only claim that it usesexclusively renewable power 83% of the time. The other 77% of the time,the power needs of the first load 710 must be met using other powersources connected to the grid 730. Similarly, if the second load 720receives power only from the second power plant 750, then the secondpower delivery profile 320 is only satisfied 83% of the time and thesecond load 720 can only claim that it uses exclusively renewable power83% of the time. The other 77% of the time, the power needs of thesecond load 720 must be met using other power sources connected to thegrid 730. However, if the first power plant 740 and the second powerplant 750 are networked and are controlled by the controller 770 via thenetwork 760, the controller 770 can direct the combined REPP output 1010to satisfy the combined power delivery profile 1020 92% of the time.This means that both the first load 710 and the second load 720 canclaim that they use only renewable power 92% of the time if the combinedREPP output 1010 is allocated equally between the first load 710 and thesecond load 720. The controller 770 may also allocate the combined REPPoutput 1010 unequally between the first load 710 and the second load 720such that the first power delivery 220 profile is satisfied more than92% of the time and the second power delivery profile 320 is satisfiedless than 92% of the time. Allocating the combined REPP output 1010between the first load 710 and the second load 720 may include notifyingthe first load 710 of an amount of power allocated to the first load andnotifying the second load 720 of an amount of power allocated to thesecond load. Allocating the combined REPP output 1010 between the firstload 710 and the second load 720 may include allocating a first portionof the power output of the first power plant 740 to the first load 710and allocating a second portion of the power output of the second powerplant 750 to the second load 720. The controller may storeconfigurations of power allocation in the memory of the controller 770.The controller may store a record of amounts of power delivered by thefirst power plant 740 and the second power plant 750 in the memory ofthe controller 770.

Networking the first power plant 740 and the second power plant 750using the controller 770 may be used to lower the initial capitalexpenditures of the first power plant 710 and the second power plant750. For example, if a reliability of 83% is all that is required by thefirst load 710 and the second load 720, then, when networked together,the first power plant 740 and the second power plant 750 may be builtwith less excess capacity than is required to by 83% reliable. The firstpower plant 740 may have an excess capacity over the maximum value ofthe first power delivery profile 220 such that the first power plant 740is 70% reliable. Similarly, the second power plant 750 may have anexcess capacity over the maximum value of the second power deliveryprofile 320 such that the second power plant 750 is 70% reliable. Thismakes the first power plant 740 and the second power plant 750 cheaperto construct than if they were both 83% reliable. The combined REPPoutput 1010 may satisfy the combined power delivery profile 1020 83%percent of the time such that the REPP output 1010 is 83% percentreliable as required by the first load 710 and the second load 720.

In some embodiments, the combined REPP output 1010 is a combination ofoutputs of a plurality of REPPs. The plurality of REPPs may include anynumber of REPPs. The greater the number of the plurality of REPPs andthe less correlated the outputs of the REPPs are, the more reliable thecombined REPP output 1010 is likely to be. Additionally and/oralternatively, the greater the number of the plurality of REPPs and theless correlated the outputs of the REPPs are, the less excess powercapacity each REPP requires for the combined REPP output 1010 to bereliable. For example, the first power plant 740 may be built such thatthe first REPP output 210 cannot satisfy the first power deliveryprofile of the first load 710 above a first threshold reliability andthe second power plant 750 may be built such that the second REPP output310 cannot satisfy the second power delivery profile of the second load720 above a second threshold reliability, but the combined REPP output1010 can still satisfy the first and second power delivery profilesabove the first and second threshold reliabilities.

The above description discusses networking power plants to aggregatetheir output, and the same approach may be used to aggregate energystorage capacity. For example, a first energy storage system (ESS) maybe sized to ensure that it can provide energy storage capacity givenfluctuating demand for energy storage capacity. The first ESS may havestorage capacity in excess of what is regularly expected to be requiredto account for large fluctuations in demand for energy storage capacity.Combining the energy storage capacity of the first ESS with the energystorage capacity of a second ESS may carry advantages similar to theadvantages of combining outputs of REPPs. The combined energy storagecapacity may be able to satisfy energy storage requirements morereliably than the energy storage capacity of the ESS and the energystorage capacity of the second ESS. The energy storage capacity of eachof the first and second ESSs may be reduced, lowering cost, whilemaintaining reliability of satisfying energy storage requirements byusing the combined energy storage capacity. The combined energy storagecapacity in excess of requirements may be used as a virtual ESS. Thevirtual ESS may provide energy storage capacity to store energy fromadditional sources.

In an example, a first battery energy storage system (BESS) may have afirst energy storage capacity and a second BESS may have a second energystorage capacity. A first power plant may have first energy storagerequirements and a second power plant may have second energy storagerequirements. Networking the first BESS and the second BESS may allowthe first BESS and the second BESS to more reliably satisfy the firstand second energy storage requirements of the first and second powerplants. Alternatively, the first and second BESSs may be smaller and/orcheaper and still satisfy the first and second energy storagerequirements of the first and second power plants at an acceptablereliability. A plurality of BESSs may be networked to amplify theseadvantages.

In another example, first and second BESSs may draw power from the gridand transfer power to the grid. The first and second BESSs may drawpower from the grid when power is less expensive and transfer power tothe grid when power is more expensive. Networking the first and secondBESSs as disclosed herein may allow the first and second BESSs to absorbspikes of power when power is less expensive to sell when power is moreexpensive. Networking the first BESS and the second BESS may allow thefirst BESS and the second BESS to capture larger spikes of power thanwould be possible if not networked. Alternatively, the first and secondBESSs may be smaller and/or cheaper and still capture larger spikes ofpower than would be possible if not networked. A plurality of BESSs maybe networked to amplify these advantages.

The above description discusses networking power plants to aggregatetheir output, and the same approach may be used to aggregate powercapacity. Operators of loads or grids may want to contract for powercapacity, the ability to deliver an amount of renewable power, whetherthe power is ultimately delivered or not. For example, a load operatormay contract for power capacity to cover a spike in power demand at theload. The power capacity is reserved for the load, and if the spike indemand occurs, the power capacity is utilized to deliver power to theload. If the spike in demand does not occur, the power capacity is notutilized to deliver power to the load. REPPs may be able to providepower capacity subject to fluctuations due to time of day, weatherconditions, state of charge of energy storage systems, and otherfactors. For example, a first REPP may be sized to ensure that it canprovide power capacity given fluctuating demand for power capacity. Thefirst REPP may have power capacity in excess of what is regularlyexpected to be required in order to account for fluctuations in powercapacity. Combining the power capacity of the first REPP with the powercapacity of a second REPP may carry advantages similar to the advantagesof combining outputs of REPPs. The combined power capacity may be ableto satisfy power capacity requirements more reliably than the powercapacity of the first REPP and the power capacity of the second REPP.The power capacity of each of the first and second REPPs may be reduced,lowering cost, while maintaining reliability of satisfying powercapacity requirements by using the combined power capacity. The combinedpower capacity in excess of requirements may be used as a virtual REPP.The virtual REPP may provide power capacity to additional loads, grids,or other customers.

FIG. 11 illustrates another example environment 1100 in accordance withone or more embodiments. The environment 1100 may include a first load710, a second load 720, and a third load 715. The environment 1100 mayinclude a grid 730, a first power plant 740, a second power plant 750, avirtual power plant 745, a network 760, and a controller 770.

The first load 710, the second load 720, and the third load 715 may beelectrically coupled to the grid 730. The first load 710, the secondload 720, and the third load 715 may be remote from each other and haveseparate power requirements. The first load 710 may have a first powerdelivery profile which details power requirements for the first load 710at different times. The second load 720 may have a second power deliveryprofile which details power requirements for the second load 720 atdifferent times. The third load 715 may have a third power deliveryprofile which details power requirements for the third load 715 atdifferent times. In some embodiments, the grid 730 may be a utility gridowned and operated by a single utility or system operator. In otherembodiments, the grid 730 may be a plurality of electrical connectionsallowing for the transmission of power from the first power plant 740and the second power plant 750 to the first load 710 and the second load720.

The first power plant 740 may be a first renewable energy power plant(REPP). The second power plant 750 may be a second REPP. The virtualpower plant 745 may represent power generated by the first power plant740 and the second power plant 750 in excess of power requirements. Thisexcess power may be allocated to different loads, functioning as thevirtual power plant 745. For example, the first power plant 740 maydeliver power to satisfy the first power delivery profile, the secondpower plant 750 may deliver power to satisfy the second power deliveryprofile, and the excess combined power output of the first power plant740 and the second power plant 750 may serve as the virtual power plant745 and be allocated to the third load 715 to satisfy the third powerdelivery profile. The first power plant 740 may have a first poweroutput that varies over time. The second power plant 750 may have asecond power output that varies over time. The virtual power plant 745may have a third power output that varies over time dependent upon thefirst power output, the second power output, and power requirementsimposed upon the first power plant 740 and the second power plant 750.The first power output and the second power output may vary differentlysuch that they are not tightly correlated. For example, the first powerplant 740 may be geographically remote from the second power plant 750such that weather patterns at the first power plant 740 differ fromweather patterns at the second power plant 750. Thus, variation in thefirst power output will not be correlated with variation in the secondpower output.

The less correlated the output of the first power plant 740 with theoutput of the second power plant 750, the greater the effects ofnetworking. The less correlated the outputs of the first power plant 740and the second power plant 750, the less variation will be present inthe combined output of the first power plant 740 and the second powerplant 750. Less variation in the combined output may result in morereliability in satisfying the power delivery profiles of the first load710 and the second load 720. Less variation in the combined output mayresult in lower capacity requirements for the first power plant 740 andthe second power plant 750. Less variation in the combined output mayresult in greater output of the virtual power plant 745.

Similar network advantages may be realized by selecting loads with powerrequirements that are not tightly correlated. For example, a combinedpower delivery profile of two loads will have less variability than theindividual power delivery profiles of the two loads if the individualpower delivery profiles are not tightly correlated. Less variability inthe combined power delivery profile allows for the combined powerdelivery profile to be served by a power plant or network of powerplants having less excess capacity. Less variability in the combinedpower delivery profile allows for a virtual power plant of a network ofpower plants to have greater output.

The first power plant 740 and the second power plant 750 may communicatewith a controller 770 via a network 760. Since the virtual power plant745 represents excess power output by the first power plant 740 and thesecond power plant 750, the controller communicates with the virtualpower plant 770 by communicating with the first power plant 740 and thesecond power plant 750. The network 760 may be any local area network(LAN) or wide area network (WAN). In some embodiments, the network isthe internet. In other embodiments, the network is a privatecommunications network.

The controller 770 may control the first power plant 740, the secondpower plant 750, and the virtual power plant 745. The controller 770 maycoordinate the first power output of the first power plant 740, thesecond power output of the second power plant 750, and the third outputof the virtual power plant 745 in order to deliver power to the firstload 710, the second load 720, and the third load 715. The controller770 may receive the first power delivery profile of the first load 710,the second power delivery profile of the second load 720, and the thirdpower delivery profile of the third load 715. In some embodiments, thecontroller 770 receives the first power delivery profile from the firstload 710, the second power delivery profile from the second load 720,and the third power delivery profile from the third load 715 via thenetwork 760. In other embodiments, the controller 770 receives the firstpower delivery profile, the second power delivery profile, and the thirdpower delivery profile from another source. The controller 770 maydirect the first power plant 740 to direct power to the first load 710or the second load 720. The controller 770 may direct the second powerplant 750 to direct power to the first load 710 or the second load 720.The controller 770 may direct the first power plant 740 to direct afirst portion of its power output to the first load 710 and a secondportion of its power output to the second load 720. The controller 770may direct the second power plant 750 to direct a third portion of itspower output to the first load 710 and a fourth portion of its poweroutput to the second load 720. The controller 770 may direct the virtualpower plant 745 to direct its power output to the third load.

The controller 770 may direct the first power plant 740 and the secondpower plant 750 to direct power to the first load 710 and the secondload 720 to satisfy the first power delivery profile and the secondpower delivery profile. If the power output of the first power plant 740is sufficient to satisfy the first power delivery profile of the firstload 710 and the power output of the second power plant 750 issufficient to satisfy the second power delivery profile of the secondload 720, the controller 770 may direct the first power plant 740 todirect sufficient power to the first load 710 to satisfy the first powerdelivery profile and direct the second power plant 750 to directsufficient power to the second load 720 to satisfy the second powerdelivery profile. If the power output of the first power plant 740 isinsufficient to satisfy the first power delivery profile of the firstload 710 and the power output of the second power plant 750 issufficient to satisfy the second power delivery profile of the secondload 720, the controller 770 may direct the first power plant 740 todirect its power output to the first load 710 and direct the secondpower plant 750 to direct sufficient power to the second load 720 tosatisfy the second power delivery profile and an amount of power to thefirst load 710 sufficient, when combined with the power output of thefirst power plant 740, to satisfy the first power delivery profile ofthe first load 710. Since the power outputs of the first power plant 740and the second power plant 750 are not tightly correlated, it is likelythat if the power output of the first power plant 740 is insufficient tosatisfy the first power delivery profile, the second power plant 750 hassufficient power output in excess of what is require by the second powerdelivery profile to supplement the power output of the first power plant740 to satisfy the first power delivery profile.

The combined power output of the first power plant 740 and the secondpower plant 750 which exceeds the first power delivery profile and thesecond power delivery profile may be directed by the controller 770 fromthe virtual power plant 745 to satisfy the third power delivery profileof the third load 715. If the combined power output of the first powerplant 740 and the second power plant 750 does not exceed the combinationof the first power delivery profile and the second power deliveryprofile, no power may be directed to satisfy the third power deliveryprofile.

In some embodiments, the first power plant 740 and the second powerplant 750 may be selected to be networked. The first power plant 740 andthe second power plant 750 may be selected for networking based on alevel of correlation between the first power output and the second poweroutput. The first power plant 740 and the second power plant 750 may beselected for networking based on a determination that the first poweroutput and the second power output are the least correlated of aplurality of power outputs of a plurality of power plants. In someembodiments, the first power output is compared to a plurality of poweroutputs to select the second power output which is the least correlatedwith the first power output of the plurality of power outputs. In otherembodiments, the first power plant 740 and the second power plant 750may be selected by optimizing for minimized correlation from a pluralityof power plants. The controller 770 may select the first power plant 740and the second power plant 750.

FIG. 12 illustrates a first REPP output 1210, a first power deliveryprofile 1220, and a first excess output 1230. The first REPP output 1210may be the first REPP output of the first power plant 740 of FIG. 11 .The first delivery profile 1220 may be the first power delivery profileof the first load 710 of FIG. 11 . The first excess output 1230 may bethe excess of the first REPP output 1210 over the first power deliveryprofile 1220. The first REPP output 1210 is shown by the dotted line,the first power delivery profile 1220 is shown by the solid line, andthe first excess output 1230 is shown by the dashed line.

FIG. 13 illustrates a second REPP output 1310, a second power deliveryprofile 1320, and a second excess output 1330. The second REPP output1310 may be the second REPP output of the second power plant 750 of FIG.11 . The second delivery profile 1320 may be the second power deliveryprofile of the second load 720 of FIG. 11 . The second excess output1330 may be the excess of the second REPP output 1310 over the secondpower delivery profile 1320. The second REPP output 1310 is shown by thedotted line, the second power delivery profile 1320 is shown by thesolid line, and the second excess output 1330 is shown by the dashedline. The second delivery profile 1320 is shown as being the same as thefirst delivery profile 1220 of FIG. 12 , but the first delivery profile1220 and the second delivery profile 1320 may be different.

FIG. 14 illustrates a combined excess output 1410 and a third powerdelivery profile 1420. The combined excess output 1410 may be acombination of the first excess output 1230 of FIG. 12 and the secondexcess output 1330 of FIG. 13 . The combined excess output 1410 may bethe output of the virtual power plant 745 of FIG. 11 . The third powerdelivery profile 1420 may be the third power delivery profile of thethird load 715 of FIG. 11 . In some embodiments, the third powerdelivery profile 1420 represents the power requirements of the thirdload 715. In other embodiments, the third power delivery profile 1420represents renewable power requested by the third load 715. The thirdpower delivery profile 1420 may be smaller than the first power deliveryprofile 1220 and the second power delivery profile 1320. The third powerdelivery profile 1420 may be based on an expected combined excess output1410. The combined excess output 1410 may be less reliable than thefirst REPP output 1210 and the second REPP output 1310. In someembodiments, the combined excess output 1410 may be directed to morethan one load and the third power delivery profile 1420 may represent acombination of power delivery profiles of various loads.

In some embodiments, the combined excess output 1410 is a combination ofexcess outputs of a plurality of REPPs. The plurality of REPPs mayinclude any number of REPPs. The greater the number of the plurality ofREPPs and the less correlated the outputs of the REPPs are, the greaterthe output and the greater the reliability of the combined excess output1410. Additionally and/or alternatively, the greater the number of theplurality of REPPs and the less correlated the outputs of the REPPs are,the less excess capacity each REPP requires for the combined excessoutput 1410 to be reliable.

FIG. 15 illustrates another example environment 1500 in accordance withone or more embodiments. The environment 1500 may include a first REPP1541, a second REPP 1542, a third REPP 1543, a fourth REPP 1544, and afifth REPP 1545. The first REPP 1541, the second REPP 1542, the thirdREPP 1543, and the fifth REPP 1545 may be solar power plants and thefourth REPP 1544 may be a wind power plant. The REPPs may be in distinctgeographical locations and be remote from each other. The outputs of theREPPs may not be tightly correlated. The REPPs may communicate with acontroller 1570 via a network. The controller 1570 may be the controller770 or play a similar role as the controller 770 of FIG. 11 .

The environment 1500 may include a first load 1511, a second load 1512,a third load 1513, a fourth load 1514, a fifth load 1515, and a sixthload 1516. The first load 1511, the second load 1512, the third load1513, the fourth load 1514, and the fifth load 1515 may behigh-reliability loads, such that they require reliable delivery ofrenewable power. The high-reliability loads may require renewable energyequal to their power requirements or equal to a portion of their powerrequirements with a reliability above a threshold reliability. Theenvironment 1500 may include a sixth load 1516. The sixth load 1516 maybe a low-reliability load, such that it does not require reliabledelivery of renewable power. Low-reliability loads may utilize renewablepower when it is available and power from other sources when renewablepower is not available. The first load 1511, the second load 1512, thethird load 1513, the fourth load 1514, the fifth load 1515, and thesixth load 1516 may be electrically coupled to the first REPP 1541, thesecond REPP 1542, the third REPP 1543, the fourth REPP 1544, and thefifth REPP 1545 via a grid 1580. The grid 1580 may be electricallycoupled to additional power sources and loads.

In some embodiments, the controller 1570 may determine power outputsetpoints for the REPPs 1541-1545. Setting the power outputs for theREPPs 1541-1545 may include receiving a first signal indicating thepower delivery profile for the first load 1511 and determining setpointsfor the REPPs 1541-1545 such that the combined power output of the REPPs1541-1545 is sufficient to satisfy the power delivery profile of thefirst load 1511. The controller 1570 may receive a second signalindicating the power delivery profile for the second load 1512 anddetermine setpoints for the REPPs 1541-1545 such that the combined poweroutput of the REPPs 1541-1545 is sufficient to satisfy the powerdelivery profiles of the first load 1511 and the second load 1512. Thecontroller 1570 may receive a signal from each of the loads 1511-1516and determine setpoints for the REPPs 1541-1545 such that the combinedpower output of the REPPs 1541-1545 is sufficient to satisfy the powerdelivery profiles of the loads 1511-1516.

The REPPs may be networked as discussed herein such that a combinedexcess output of the REPPs in excess of the requirements of thehigh-reliability loads functions as a virtual power plant. The virtualpower plant may direct power to the sixth load 1516.

In an example, if the combined output of the REPPs 1541-1545 is morethan the sum of power delivery profiles of loads 1511-1516, thecontroller 1570 may set power outputs for the REPPs 1541-1545 equal to acombined power delivery profile of the loads 1511-1516. The controller1570 may notify the loads 1511-1516 that the power delivered to theloads 1511-1516 from the REPPs 1541-1545 via the grid was sufficient tosatisfy their power delivery profiles.

In another example, if the combined output of the REPPs 1541-1545 ismore than the sum of the power delivery profiles of the loads 1511-1515,but not more than the sum of the power delivery profiles of the loads1511-1516, the controller 1570 may set power outputs for the REPPs1541-1545 equal to maximum current power outputs for the REPPs1541-1545. The controller 1570 may allocate power to the loads 1511-1515sufficient to satisfy their power delivery profiles and notifies theloads 1511-1515 that the power delivered to the loads 1511-1515 wassufficient to satisfy their power delivery profiles. The controller 1570may allocate a remainder of the combined output of the REPPs 1541-1545to the sixth load 1516 and notifies the sixth load 1516 of an amount ofthe remainder of the combined output of the REPPs 1541-1545 which wasdelivered to the sixth load 1516.

In yet another example, if the combined output of the REPPs 1541-1545 isless than the sum of the power delivery profiles of loads 1511-1515, thecontroller 1570 may set power outputs for the REPPs 1541-1545 equal tomaximum current power outputs for the REPPs 1541-1545. The controller1570 may allocate power to the loads 1511-1515 and notify the loads1511-1515 of amounts of power delivered to the loads 1511-1515 andwhether the amounts of power delivered to the loads 1511-1515 weresufficient to satisfy their power delivery profiles. The controller 1570may notify the sixth load 1516 that no power was delivered to the sixthload 1516 from the REPPs 1541-1545.

FIG. 16 is a flowchart of an example method 1600 for allocating powerfrom networked power plants in accordance with one or more embodiments.Additional, fewer, or different operations may be performed in themethod, depending on the embodiment. Further, the operations may beperformed in the order shown, concurrently, or in a different order.

At 1610, a controller receives a first power delivery profile for afirst load. The controller may store the first power delivery profile ina memory of the controller. The power delivery profile may represent arequest for amounts of power at different times. For example, a loaddesiring to use only renewable energy may have a power delivery profileequal to its power requirements. At 1620, the controller receives asecond power delivery profile for a second load. The controller maystore the second power delivery profile in the memory. The second powerdelivery profile may be the same or different from the first powerdelivery profile. At 1630, the controller may determine a power outputcapability of a first power plant and a power output capability of asecond power plant. The first power plant and the second power plant maybe renewable energy power plants (REPPs). The controller may store thepower output capabilities of the first and second power plants in thememory. Determining the power output capabilities of the first andsecond power plants may include receiving an indication of the poweroutput capabilities of the first and second power plants via a network.In some embodiments, the power output capabilities of the first andsecond power plants may be predictions of power outputs of the first andsecond power plants. In other embodiments, the power output capabilitiesof the first and second power plants may be current maximum outputcapabilities of the first and second power plants.

At 1640, the controller sets a first power output for the first powerplant and a second power output for the second power plant based on thepower delivery profiles of the first and second loads and the poweroutput capabilities of the first and second power plants. Setting thefirst and second power outputs may include determining a combined poweroutput capability of the first and second power plants and a combinedpower delivery profile of the first and second loads. The controller maydetermine whether the combined power output capability is sufficient tosatisfy the combined power delivery profile. The controller may comparethe combined power output capability to the combined power deliveryprofile and determine points where the combined power output capabilityexceeds the combined power delivery profile. The controller may set thefirst power output and the second power output such that the combinedpower output satisfies the combined power delivery profile. Setting thefirst power output and the second power output may include sending anindication to the first and second power plants of power output levelsat different times. For example, if the power output capability of thefirst power plant exceeds the first power delivery profile by an amountsufficient to compensate for a deficiency in the power output capabilityof the second power plant, the controller will set the second poweroutput to a maximum possible amount and the first power output to anamount sufficient to satisfy the first power delivery profile and thesecond power delivery profile when combined with the second poweroutput. In some embodiments, the controller may set the power outputs ofthe first and second power plants in real time. In other embodiments,the controller may set the power outputs of the first and second powerplants for a time period.

At 1650, the controller allocates the power outputs of the first andsecond power plants to the first and second loads. In some embodiments,allocating the power outputs of the first and second power plants to thefirst and second loads includes notifying the first load of a firstamount of power allocated to the first load and whether the first amountof power is sufficient to satisfy the first power delivery profile andnotifying the second load of a second amount of power allocated to thesecond load and whether the second amount of power is sufficient tosatisfy the second power delivery profile.

At 1660, power is delivered to the first load and the second load. Thecontroller may direct the first power plant and the second power plantto deliver the allocated power outputs to the first and second loads.The first and second power plants may deliver the allocated poweroutputs to the first and second loads via a grid. In some embodiments,delivering the power outputs of the first and second power plants to thefirst and second loads includes notifying the first load of a firstamount of power delivered to the first load and whether the first amountof power is sufficient to satisfy the first power delivery profile andnotifying the second load of a second amount of power delivered to thesecond load and whether the second amount of power is sufficient tosatisfy the second power delivery profile.

FIG. 17 is a flowchart of an example method 1700 for delivering powerusing a virtual power plant in accordance with one or more embodiments.Additional, fewer, or different operations may be performed in themethod, depending on the embodiment. Further, the operations may beperformed in the order shown, concurrently, or in a different order.

At 1710, a controller receives a power delivery profile for each of afirst load and a second load. The power delivery profile for each loadmay represent a request for amounts of power at different times. Forexample, a load desiring to use only renewable energy may have a powerdelivery profile equal to its power requirements.

The controller may store the power delivery profile of the first andsecond load in a memory of the controller. At 1720, the controllerdetermines a power output capability of a first power plant and a poweroutput capability of a second power plant. The first power plant and thesecond power plant may be renewable energy power plants (REPPs).Determining the power output capabilities of the first and second powerplants may include receiving an indication of the power outputcapabilities of the first and second power plants via a network. In someembodiments, the power output capabilities of the first and second powerplants may be predictions of power outputs of the first and second powerplants. In other embodiments, the power output capabilities may of thefirst and second power plants may be current maximum output capabilitiesof the first and second power plants. The controller may store the poweroutput capabilities of the first and second power plants in the memory.

At 1730, the controller determines a first amount of a combined poweroutput capability of the first and second power plants in excess of thepower delivery profile of the first load. Determining the first amountof the combined power output capability may include combining the poweroutput capabilities of the first and second power plants to obtain thecombined power output capability and comparing, using a processor of thecontroller, the combined power output capability to the power deliveryprofile of the first load. Power that is not needed to satisfy the powerdelivery profile of the first load is power produced in excess of thepower delivery profile of the first load. The excess power output may betreated as a virtual power plant which may direct power to loads. Thecontroller may store an indication of the excess power output in thememory. At 1740, the controller allocates a second amount of thecombined output capability equal to the power delivery profile of thefirst load to the first load. In some embodiments, allocating the secondamount of power to the first load includes notifying, by the controller,the first load of the amount of power allocated to the first load. Thecontroller allocates sufficient power to the first load to satisfy thepower delivery profile of the first load. At 1750, the controllerallocates the first amount of power to the second load. In someembodiments, allocating the first amount of power to the second loadincludes notifying, by the controller, the second load of the amount ofpower allocated to the second load.

At 1760, the controller directs the first and second power plants todeliver the second amount of power to the first load and the firstamount of power to the second load. In some embodiments, the controllerdirects the virtual power plant representing the excess power of thecombined output capability to direct the first amount of power to thesecond load. The controller may direct the first, second, and virtualpower plants via a network. The first, second, and virtual power plantsmay deliver power via a grid. In some embodiments, delivering the firstamount of power to the second load includes notifying, by thecontroller, the second load of the amount of power allocated to thesecond load. In some embodiments, delivering the second amount of powerto the first load includes notifying, by the controller, the first loadof the amount of power allocated to the first load.

The embodiments disclosed herein represent various technicalimprovements. The specific implementation of setting power outputs ofREPPs based on power delivery profiles and allocating power outputs todifferent loads is a solution to problems in delivering renewable energyover a grid. Previous methods for delivering renewable energy requiredlocal power generation and direct transmission of power from the REPP tothe load. Connecting a load to a grid did not allow for the use ofpurely renewable energy because renewable power and non-renewable powerare commingled on the grid. To deliver renewable power over a gridrequired an REPP to deliver an amount of power to the grid and allocateits output to a load, which would draw power from the grid equal to theamount of power delivered to the grid by the REPP. The REPP, due tofluctuations in power generation, would have to be oversized relative topower requirements of the load in order to reliably satisfy the powerrequirements. In contrast, the embodiments discussed herein offer thetechnical improvement of more efficiently allocating specific poweroutputs of networked REPPs to specific loads in order to more reliablyand more efficiently satisfy the power requirements of the specificloads. More efficiently allocating the specific power outputs ofnetworked REPPs to specific loads in order to satisfy the powerrequirements of the specific loads is a practical application thatlowers construction and maintenance costs of the networked power plants.The embodiments discussed herein offer the technical improvement ofallocating a combined power output of REPPs to specific loads to morereliably and efficiently satisfy the power requirements of the specificloads. Allocations of specific power outputs to specific loads may bestored in the memory of the controller. The controller may communicatethe allocations to the loads over the network. The embodiments hereinalso provide for the practical application of providing energy productssuch as energy storage and power capacity associated with particularloads, power sources, and attributes. For example, the technicalimprovement of allocating specific power output of a specific REPP to aspecific load allows that specific power output to be tracked anddelivered to the specific load.

The technical improvement of more efficiently allocating outputs ofREPPs to loads provides for the practical application of an operator ofmultiple REPPs contracting with loads for the delivery of power. Insteadof each operator of individual REPPs contracting to sell an amount ofpower allocated to a load, the operator of multiple REPPs can contractto sell a combined output of the multiple REPPs allocated to multipleloads. This results in more reliable delivery of renewable power as thecombined output has less variability than outputs of individual REPPs.These technical improvements allow for greater flexibility and usercustomization in contracting for power than previous systems andmethods.

Networking power plants to combine their outputs bears significantadvantages over conventional systems. Networking power plants to combinetheir outputs provides the technical improvement of greater reliabilityof power output. Networking power plants improves the functioning ofpower plants by reducing the strain of power output fluctuations onindividual plants. Networking power plants provides the technicalimprovement of allowing individual power plants to be built with lessexcess power output capacity. The practical application of thistechnical improvement is in reducing the cost of renewable power bybuilding smaller REPPs with less excess power output capacity over powerrequirements. Networking power plants provides the technical improvementof utilizing excess combined power output as a virtual power plant. Thishas the practical application of providing renewable power to additionalloads using excess power output that would not otherwise be delivered toa load.

Networked power plants may take advantage of solar forecasting tocoordinate their outputs. Incorporating solar forecasting into thecoordination of networked power plants has the technical advantage ofproviding more accurate predictions of power outputs of networked powerplants. Utilizing more accurate predictions of power outputs ofnetworked power plants allows for the combined output of networked powerplants to be lower than it would be with less accurate predictions ofpower outputs the networked power plants. Outputs of each power plant ofthe networked power plants may be adjusted based on solar forecasts suchthat variability in the outputs of each power plant of the networkedpower plants caused by shadows or shade do not affect a variability ofthe combined output of the networked power plants. In addition,utilizing solar forecasting to coordinate the outputs of networked powerplants solves the technical problem of ramping up or down power outputsof individual power plants of the networked power plants at ratessufficient to satisfy load power requirements. Without utilizing solarforecasting, sudden output decreases at first power plants due to shadowor shade may not be able to be compensated for with complementary outputincreases at second power plants due to limitations of maximum ramp-uprates of the second power plants. Utilizing solar forecasting allows thesecond power plants to ramp up their outputs in anticipation of outputdecreases at the first power plants due to shadow or shade. Utilizingsolar forecasting allows networked power plants to ramp up and downtheir output at rates that increase the useful lifespan of RESs and ESSsof the networked power plants.

FIG. 18 is a flowchart of an example method 1800 for delivering powerfrom networked power plants using solar forecasting. Additional, fewer,or different operations may be performed in the method, depending on theembodiment. Further, the operations may be performed in the order shown,concurrently, or in a different order.

At 1810, a controller of a plurality of networked power plants asdescribed herein obtains irradiance data at a first time and a secondtime from a plurality of sensors. In some embodiments, the sensors maybe disposed among or adjacent the networked power plants. For example,the sensors may be disposed between solar modules of the networked powerplants and along or adjacent to the perimeter of grids of solar modulesof the networked power plants. There may be at least about 1 solarmodule per sensor, 2 solar modules per sensor, 3 solar modules persensor, 4 solar modules per sensor, 5 solar modules per sensor, 10 solarmodules per sensor, 20 solar modules per sensor, or more. The sensorsmay be irradiance meters. In other embodiments, the sensors may bedisposed over a geographic area. For example, the sensors may bedisposed in a grid over a geographic area. In another example, thesensors may be part of rooftop solar units distributed throughout acity.

In some embodiments, inverters that are used to convert DC powergenerated by solar modules to AC power may be used as sensors. Theinverters may be disposed among arrays of solar modules of the networkedpower plants, and a particular inverter may be connected to a subset ofadjacent solar modules. The inverters may have built-in sensors that areconfigured to measure electric power. For example, the sensors may becomponents of a supervisory control and data acquisition (SCADA) systemof the inverters. The irradiance of the solar modules that are connectedto a particular inverter can be inferred from the power output of thatinverter. The use of inverters as sensors may be advantageous because itmay allow the implementation of the forecasting system described hereinwithout specialized or dedicated hardware.

The first time may be before the second time. The first time and thesecond time may be separated by any unit of time. For example, the firsttime and the second time may be separated by one second to measure thevelocity of a shadow cast by a cloud. In another example, the first timeand the second time may be separated by one year to measure shade castby stationary objects such as buildings at a particular time of year.

At 1820, the controller determines whether one or more solar modules ofa plurality of networked power plants will be covered by a shadow orshade at a third time based on the irradiance data. The third time maybe after the second time. The first time and the second time may beseparated by any unit of time. For example, the second time and thethird time may be separated by 1 second to predict whether adjacentsolar modules will be shaded by a passing cloud. In another example, thesecond time and the third time may be separated by one year to predicthow solar modules of the plurality of networked power plants will beshaded by stationary objects such as buildings at a particular time ofyear.

The controller may be configured to determine whether the one or moresolar modules of the plurality of networked power plants will be coveredby a shadow or shade at the third time by determining a position and ashape of the shadow or shade at the first or second time. The controllermay be configured to determine whether the one or more solar modules ofthe plurality of networked power plants will be covered by a shadow orshade at the third time by determining a velocity of the shadow orshade. For example, the controller may determine that a circular shadowcast by a cloud is above a first subset of solar modules of a firstpower plant of the plurality of networked power plants and, based on avelocity of the shadow, the shadow will be above a second subset ofsolar modules of the first power plant at the third time. In anotherexample, the controller may determine that a circular shadow cast by acloud is above a first subset of solar modules of a first power plant ofthe plurality of networked power plants and, based on a velocity of theshadow, the shadow will be above a second subset of solar modules of asecond power plant of the plurality of networked power plants at thethird time. In yet another example, the controller may determine that ashadow cast by a mountain shades a first subset of solar modules of afirst power plant of the plurality of networked power plants and, basedon a velocity of the shadow, the shadow will be above a second subset ofsolar modules of a second power plant of the plurality of networkedpower plants at the third time.

At 1830, the controller may generate, based at least in part on thedetermination, a power output prediction for each power plant of theplurality of networked power plants at the third time. In someembodiments, the controller may calculate an output for each power plantof the plurality of networked power plants by determining a predictedirradiance for each solar module of each power plant and multiplying thepredicted irradiance by a conversion factor for each solar module ofeach power plant. In other embodiments, the controller may calculate anoutput for each power plant of the plurality of networked power plantsby determining a predicted irradiance for each solar array of each powerplant and multiplying the predicted irradiance by a conversion factorfor each solar array of each power plant. In yet other embodiments, thecontroller may calculate an output for each power plant of the pluralityof networked power plants by determining a predicted irradiance for eachpower plant and multiplying the predicted irradiance by a conversionfactor for each power plant.

At 1840, the controller may receive a first power delivery profile for afirst load and a second power delivery profile for a second load. Thefirst load may have a first power delivery profile which details powerrequirements for the first load at different times. The second load mayhave a second power delivery profile which details power requirementsfor the second load at different times. For example, the first powerdelivery profile may detail that the first load requires 50 MW from 9A.M. to 5 P.M. and the second load requires 10 MW from 9 A.M. to 5 P.M.and 70 MW from 5 P.M. to 8 P.M. In another example, the first powerdelivery profile may be similar to the first power delivery profile 820of FIG. 8 and the second power delivery profile may be similar to thesecond power delivery profile 920 of FIG. 9 .

At 1850, the controller may adjust a power output of one or more powerplants of the plurality of networked power plants based at least in parton the power output prediction, the power delivery profile for the firstload, and the power delivery profile for the second load. The controllermay adjust a power output of a first plant upward based on the poweroutput prediction of a second plant being lowered due to shadow andshade. The controller may adjust the power output of the first plantupward to compensate for the lowered predicted output of the secondplant. The controller may be configured to adjust the power output ofthe one or more of the plurality of networked power plants such that thecombined power output of the plurality of networked power plantssatisfies the power delivery profile for the first load and the powerdelivery profile for the second load. The controller may balancecontributions from the plurality of networked power plants to thecombined output to maintain the combined output despite fluctuations inoutput of individual power plants due to shade or shadow.

In some embodiments, the controller is configured to adjust the poweroutput of the one or more of the plurality of networked power plantssuch that a variability of the combined output of the plurality ofnetworked power plants is less than a variability of an output of eachpower plant of the plurality of networked power plants. Variability maybe introduced into the output of a power plant by shade or shadow, butthe controller may balance contributions from the plurality of networkedpower plants to the combined output such that the increased variabilitydue to shade or shadow is not reflected in the combined output. Thecombined output may be kept steady throughout fluctuations in outputs ofindividual plants due to shade or shadow.

In some embodiments, the controller is configured to adjust the poweroutput of the one or more power plants of the plurality of networkedpower plants by adjusting a charge/discharge of an energy storage system(ESS) of the one or more power plants of the plurality of networkedpower plants. For example, a first power plant may increase its outputto compensate for a lowered predicted output of a second power plant dueto shade or shadow. The first power plant may increase its output bydrawing power from an ESS of the first power plant. The ESS dischargemay be equal to an amount of lowered output from the second power plant.In another example, a first power plant may have a lowered predictedoutput due to shade or shadow. The first power plant may compensate fora portion of its lowered predicted output by discharging a first ESSassociated with the first power plant. A second power plant maycompensate for the remainder of the lowered predicted output of thefirst power plant by reducing a rate of charge of a second ESSassociated with the second power plant such that an output of the secondpower plant increases to compensate for the remainder of the loweredpredicted output of the first power plant. The controller may sendsignals to the plurality of networked power plants to adjust acharge/discharge of each ESS associated with the networked power plants.To increase output, an ESS charge may be decreased or an ESS dischargeincreased. A variety of combinations of ESS charge decreases and ESSdischarge increases may be utilized to increase output to compensate forfluctuations in output of networked power plants due to shade or shadow.

In some embodiments, the controller is configured to adjust the poweroutput of the one or more power plants of the plurality of networkedpower plants such that ramp-up rates and ramp-down rates of theplurality of networked power plants are within a predefined range. Inother embodiments, the controller is configured to adjust the poweroutput of the one or more power plants of the plurality of networkedpower plants to optimize ramp-up rates and ramp-down rates according toan effect of the ramp-up rates and the ramp-down rates on a longevity ofcomponents of the plurality of networked power plants. For example, thecontroller may adjust the power output of the one or more power plantsof the plurality of networked power plants such that the ramp-up ratesand ramp-down rates are as slow as possible.

At 1860, the controller allocates a combined power output of theplurality of networked power plants to the first and second loads.Allocating the combined power output may include matching power usage bythe first and second loads to outputs of the plurality of networkedpower plants. Allocating the combined power output may include assigningthe combined power output to the first and second loads. In someembodiments, the controller is configured to deliver the allocatedcombined output to the first load and the second load via a grid. Thecontroller may be configured to send signals to the plurality ofnetworked power plants to deliver power over the grid. The controllermay allocate the combined power output to the first and second loads bycommunicating to the first load a first amount of power delivered to thefirst load and communicating to the second load a second amount of powerdelivered to the second load. For example, the plurality of power plantsmay produce 80 MW of power delivered to a grid. A factory may use 70 MWof power from the grid and a home may use 20 MW of power from the grid.The controller may communicate to the factory that 70 MW of the 80 MWproduced by the plurality of power plants was allocated to and deliveredto the factory. The controller may communicate to the home that 10 MW ofthe 80 MW produced by the plurality of power plants was allocated to anddelivered to the home.

The controller may allocate power to the first and second loads based onthe power delivery profiles of the first and second loads. In someembodiments, the controller may adjust how much power is delivered toeach load based on the power output prediction for each power plant. Forexample, the controller may allocate less power to each load if thecombined power output is lowered due to shade or shadow. In anotherexample, the controller may allocate less power to only certain loads ifthe combined power output is lowered due to shade or shadow. In yetanother example, the controller may allocate reduced amounts of power toloads according to a ranking of the loads. The ranking of loads may bebased on power purchase agreements between the plurality of power plantsand the loads.

In an illustrative embodiment, any of the operations described hereincan be implemented at least in part as computer-readable instructionsstored on a computer-readable memory. Upon execution of thecomputer-readable instructions by a processor, the computer-readableinstructions can cause a node, such as a computing node or a power plantnode, to perform the operations.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected,” or“operably coupled,” to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable,” to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to inventions containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations. In addition, evenif a specific number of an introduced claim recitation is explicitlyrecited, those skilled in the art will recognize that such recitationshould typically be interpreted to mean at least the recited number(e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations). Furthermore, in those instances where a conventionanalogous to “at least one of A, B, and C, etc.” is used, in generalsuch a construction is intended in the sense one having skill in the artwould understand the convention (e.g., “a system having at least one ofA, B, and C” would include but not be limited to systems that have Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). In those instances where aconvention analogous to “at least one of A, B, or C, etc.” is used, ingeneral such a construction is intended in the sense one having skill inthe art would understand the convention (e.g., “a system having at leastone of A, B, or C” would include but not be limited to systems that haveA alone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). It will be furtherunderstood by those within the art that virtually any disjunctive wordand/or phrase presenting two or more alternative terms, whether in thedescription, claims, or drawings, should be understood to contemplatethe possibilities of including one of the terms, either of the terms, orboth terms. For example, the phrase “A or B” will be understood toinclude the possibilities of “A” or “B” or “A and B.” Further, unlessotherwise noted, the use of the words “approximate,” “about,” “around,”“similar,” “substantially,” etc., mean plus or minus ten percent.

The foregoing description of illustrative embodiments has been presentedfor purposes of illustration and of description. It is not intended tobe exhaustive or limiting with respect to the precise form disclosed,and modifications and variations are possible in light of the aboveteachings or may be acquired from practice of the disclosed embodiments.It is intended that the scope of the invention be defined by the claimsappended hereto and their equivalents.

The foregoing outlines features of several embodiments so that thoseskilled in the art may better understand the aspects of the presentdisclosure. Those skilled in the art should appreciate that they mayreadily use the present disclosure as a basis for designing or modifyingother processes and structures for carrying out the same purposes and/orachieving the same advantages of the embodiments introduced herein.Those skilled in the art should also realize that such equivalentconstructions do not depart from the spirit and scope of the presentdisclosure, and that they may make various changes, substitutions, andalterations herein without departing from the spirit and scope of thepresent disclosure.

What is claimed is:
 1. A method comprising: receiving a power deliveryprofile for each of a first load and a second load; determining a firstpower output capability of a first power plant and a second powercapability for a second power plant; determining a first amount of acombined power output capability of the first and second power plants inexcess of the power delivery profile of the first load; allocating asecond amount of the combined power output capability equal to the powerdelivery profile of the first load to the first load; allocating thefirst amount of power to the second load; and delivering the secondamount of power to the first load and the first amount of power to thesecond load.
 2. The method of claim 1, wherein the power deliveryprofile of the first load equals power requirements for the first load.3. The method of claim 1, wherein the first power plant and the secondpower plant are renewable energy power plants (REPPs).
 4. The method ofclaim 1, wherein the first power output capability and the second powercapability are predictions of power outputs of the first power plant andthe second power plant.
 5. The method of claim 1, further comprisingnotifying the first load of an amount of power allocated to the firstload.
 6. The method of claim 1, further comprising notifying the secondload of an amount of power allocated to the second load.
 7. The methodof claim 1, wherein determining the first power output capability andthe second power capability includes receiving a first indication of thefirst power output capability and a second indication of the secondpower capability via a network.
 8. A non-transitory computer-readablemedia comprising computer-executable instructions embodied thereon that,when executed by a processor, cause the processor to perform a processcomprising: receiving a power delivery profile for each of a first loadand a second load; determining a first power output capability of afirst power plant and a second power capability for a second powerplant; determining a first amount of a combined power output capabilityof the first and second power plants in excess of the power deliveryprofile of the first load; allocating a second amount of the combinedpower output capability equal to the power delivery profile of the firstload to the first load; allocating the first amount of power to thesecond load; and delivering the second amount of power to the first loadand the first amount of power to the second load.
 9. The non-transitorycomputer-readable media of claim 8, wherein the power delivery profileof the first load equals power requirements for the first load.
 10. Thenon-transitory computer-readable media of claim 8, wherein the firstpower plant and the second power plant are renewable energy power plants(REPPs).
 11. The non-transitory computer-readable media of claim 8,wherein the first power output capability and the second powercapability are predictions of power outputs of the first power plant andthe second power plant.
 12. The non-transitory computer-readable mediaof claim 8, further comprising notifying the first load of an amount ofpower allocated to the first load.
 13. The non-transitorycomputer-readable media of claim 8, further comprising notifying thesecond load of an amount of power allocated to the second load.
 14. Thenon-transitory computer-readable media of claim 8, wherein determiningthe first power output capability and the second power capabilityincludes receiving a first indication of the first power outputcapability and a second indication of the second power capability via anetwork.
 15. A system comprising: a renewable energy source (RES); anenergy storage system (ESS); and a controller coupled to the RES and ESSconfigured to: receive a power delivery profile for each of a first loadand a second load; determine a first power output capability of a firstpower plant and a second power capability for a second power plant;determine a first amount of a combined power output capability of thefirst and second power plants in excess of the power delivery profile ofthe first load; allocate a second amount of the combined power outputcapability equal to the power delivery profile of the first load to thefirst load; allocate the first amount of power to the second load; anddeliver the second amount of power to the first load and the firstamount of power to the second load.
 16. The system of claim 15, whereinthe power delivery profile of the first load equals power requirementsfor the first load.
 17. The system of claim 15, wherein the first poweroutput capability and the second power capability are predictions ofpower outputs of the first power plant and the second power plant. 18.The system of claim 15, wherein the controller is further configured tonotify the first load of an amount of power allocated to the first load.19. The system of claim 15, wherein the controller is further configuredto notify the second load of an amount of power allocated to the secondload.
 20. The system of claim 15, wherein the controller is furtherconfigured to determine the first power output capability and the secondpower capability includes receiving a first indication of the firstpower output capability and a second indication of the second powercapability via a network.